120 research outputs found

    Enhancing Prostate Cancer Diagnosis with Deep Learning: A Study using mpMRI Segmentation and Classification

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    Prostate cancer (PCa) is a severe disease among men globally. It is important to identify PCa early and make a precise diagnosis for effective treatment. For PCa diagnosis, Multi-parametric magnetic resonance imaging (mpMRI) emerged as an invaluable imaging modality that offers a precise anatomical view of the prostate gland and its tissue structure. Deep learning (DL) models can enhance existing clinical systems and improve patient care by locating regions of interest for physicians. Recently, DL techniques have been employed to develop a pipeline for segmenting and classifying different cancer types. These studies show that DL can be used to increase diagnostic precision and give objective results without variability. This work uses well-known DL models for the classification and segmentation of mpMRI images to detect PCa. Our implementation involves four pipelines; Semantic DeepSegNet with ResNet50, DeepSegNet with recurrent neural network (RNN), U-Net with RNN, and U-Net with a long short-term memory (LSTM). Each segmentation model is paired with a different classifier to evaluate the performance using different metrics. The results of our experiments show that the pipeline that uses the combination of U-Net and the LSTM model outperforms all other combinations, excelling in both segmentation and classification tasks.Comment: Accepted at CISCON-202

    Liquid-liquid equilibrium and partitioning features of bovine trypsin in Ucon 50 HB5100 /sodium citrate aqueous two phase systems

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    The phase diagrams of Ucon 50-HB-5100, a non-ionic random copolymer of ethylene oxide and propylene oxide (EOPO) and sodium citrate aqueous two-phase systems were determined at different pHs (5.20 and 8.20) and temperatures (5, 20 and 40º C). The binodal curves were determined by refractive index and enzymatic assay of the solution and described using a four-parameter sigmoidal equation, the reliability of the measured tie line compositions was ascertained by correlation equations given by Othmer Tobias and Bancroft. The two-phase area was expanded by increasing both pH and temperature. The partitioning of bovine trypsin and a-chymotrypsin, proteases of similar physico-chemical properties was investigated in order to evaluate the applicability of partitioning as a putative method to isolate from pancreas and to obtain any information about their partitioning mechanism. The effect of different factors such as pH, tie line length and the presence of an inorganic salt on the protein partition coefficient were analyzed.Se caracterizaron las curvas binomiales correspondientes a los sistemas bifásicos acuosos formados por Ucon 50-HB-5100, un copolímero al azar de óxido de etileno y óxido de propileno (EOPO) y citrato de sodio a diferentes pHs (5,20 y 8,20) y temperaturas (5, 20 y 40º C). Las curvas binomiales se obtuvieron por determinación del índice de refracción y ensayos enzimáticos de las soluciones correspondientes; las composiciones de las líneas de unión se corroboraron por las ecuaciones propuestas por Othmer Tobias y Bancroft. El aumento del pH y la temperatura condujeron a un aumento del área bifásica. También se ensayó el comportamiento de reparto de dos proteasas tripsina y α-quimotripsina con el objetivo de emplear los principios de partición como método de aislamiento y purificación de Tripsina a partir de páncreas bovino y de obtener información acerca del mecanismo de partición de la misma. Se analizó el efecto del pH, longitud de la línea de unión y presencia de sales inorgánicas sobre el coeficiente de partición de las enzimas

    Liquid–liquid equilibrium of the Ucon 50-HB5100/sodium citrate aqueous two-phase systems

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    The phase diagrams of Ucon 50-HB5100/sodium citrate aqueous two-phase systems were determined at 5, 20 and 40 ◦C. Two medium pHs 5.20 and 8.20 were assayed. The binodal curves were satisfactorily described using a four-parameter sigmoidal equation. The two-phase area was expanded by increasing both pH and temperature. The reliability of the measured tie line compositions was ascertained by correlation equations given by Othmer–Tobias and Bancroft.VALNATURACONICETALFA II-0440-FA-Exchange programme between Universities of the European Union and Latin Americ

    Maternal Risk Factors Associated with Hypospadias

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    AbstractIntroduction: Epidemiological studies have elucidated maternal and fetal factors that are associated with an increased risk of hypospadias .This study examined the association of hypospadias risk with several maternal reproductive and demographic characteristics: age, parity, body mass index (BMI), nausea and vomiting of pregnancy, fertility treatments , education and diet .Materials and Methods: Mothers of children with hypospadias were invited to participate in this case control study. Participating mothers completed a self administered questionnaire or a social worker administered/assisted questionnaire. Mothers of age matched children without hypospadias acted as controls and they too similarly completed the same questionnaire.Results: The risk factors associated with hypospadias were maternal age, primiparity , previous fertility treatment and nausea and vomiting of pregnancy .Conclusions: Increased maternal age, primiparity and previous fertility treatments in mothers are associated with an increased risk of hypospadias in male offsprings.Keywords: Hypospadias, Maternal age, Parity, Fertility, Maternal education, Nausea and vomitin

    An order-to-disorder structural switch activates the FoxM1 transcription factor

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    Intrinsically disordered transcription factor transactivation domains (TADs) function through structural plasticity, adopting ordered conformations when bound to transcriptional co-regulators. Many transcription factors contain a negative regulatory domain (NRD) that suppresses recruitment of transcriptional machinery through autoregulation of the TAD. We report the solution structure of an autoinhibited NRD-TAD complex within FoxM1, a critical activator of mitotic gene expression. We observe that while both the FoxM1 NRD and TAD are primarily intrinsically disordered domains, they associate and adopt a structured conformation. We identify how Plk1 and Cdk kinases cooperate to phosphorylate FoxM1, which releases the TAD into a disordered conformation that then associates with the TAZ2 or KIX domains of the transcriptional co-activator CBP. Our results support a mechanism of FoxM1 regulation in which the TAD undergoes switching between disordered and different ordered structures

    Pollutant-Induced Modulation in Conformation and β-Lactamase Activity of Human Serum Albumin

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    Structural changes in human serum albumin (HSA) induced by the pollutants 1-naphthol, 2-naphthol and 8-quinolinol were analyzed by circular dichroism, fluorescence spectroscopy and dynamic light scattering. The alteration in protein conformational stability was determined by helical content induction (from 55 to 75%) upon protein-pollutant interactions. Domain plasticity is responsible for the temperature-mediated unfolding of HSA. These findings were compared to HSA-hydrolase activity. We found that though HSA is a monomeric protein, it shows heterotropic allostericity for β-lactamase activity in the presence of pollutants, which act as K- and V-type non-essential activators. Pollutants cause conformational changes and catalytic modifications of the protein (increase in β-lactamase activity from 100 to 200%). HSA-pollutant interactions mediate other protein-ligand interactions, such as HSA-nitrocefin. Therefore, this protein can exist in different conformations with different catalytic properties depending on activator binding. This is the first report to demonstrate the catalytic allostericity of HSA through a mechanistic approach. We also show a correlation with non-microbial drug resistance as HSA is capable of self-hydrolysis of β-lactam drugs, which is further potentiated by pollutants due to conformational changes in HSA

    A Prognostic Model for Estimating the Time to Virologic Failure in HIV-1 Infected Patients Undergoing a New Combination Antiretroviral Therapy Regimen

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    <p>Abstract</p> <p>Background</p> <p>HIV-1 genotypic susceptibility scores (GSSs) were proven to be significant prognostic factors of fixed time-point virologic outcomes after combination antiretroviral therapy (cART) switch/initiation. However, their relative-hazard for the time to virologic failure has not been thoroughly investigated, and an expert system that is able to predict how long a new cART regimen will remain effective has never been designed.</p> <p>Methods</p> <p>We analyzed patients of the Italian ARCA cohort starting a new cART from 1999 onwards either after virologic failure or as treatment-naïve. The time to virologic failure was the endpoint, from the 90<sup>th </sup>day after treatment start, defined as the first HIV-1 RNA > 400 copies/ml, censoring at last available HIV-1 RNA before treatment discontinuation. We assessed the relative hazard/importance of GSSs according to distinct interpretation systems (Rega, ANRS and HIVdb) and other covariates by means of Cox regression and random survival forests (RSF). Prediction models were validated via the bootstrap and c-index measure.</p> <p>Results</p> <p>The dataset included 2337 regimens from 2182 patients, of which 733 were previously treatment-naïve. We observed 1067 virologic failures over 2820 persons-years. Multivariable analysis revealed that low GSSs of cART were independently associated with the hazard of a virologic failure, along with several other covariates. Evaluation of predictive performance yielded a modest ability of the Cox regression to predict the virologic endpoint (c-index≈0.70), while RSF showed a better performance (c-index≈0.73, p < 0.0001 vs. Cox regression). Variable importance according to RSF was concordant with the Cox hazards.</p> <p>Conclusions</p> <p>GSSs of cART and several other covariates were investigated using linear and non-linear survival analysis. RSF models are a promising approach for the development of a reliable system that predicts time to virologic failure better than Cox regression. Such models might represent a significant improvement over the current methods for monitoring and optimization of cART.</p
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